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Record W2085025319 · doi:10.1063/1.3549153

Power performance of canted blades for a vertical axis wind turbine

2011· article· en· W2085025319 on OpenAlexaff
Shawn Armstrong, Stephen Tullis

Bibliographic record

VenueJournal of Renewable and Sustainable Energy · 2011
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsVertical axis wind turbineAerodynamicsThrustWind powerTurbine bladeTurbineMarine engineeringBlade pitchWind tunnelPower (physics)EngineeringVertical axisHorizontal axisStructural engineeringAerospace engineeringMechanical engineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Small scale vertical axis wind turbines have a number of advantages for deployment in an urban environment but are subject to highly varying thrust and radial aerodynamic forces. Helical blade shapes for vertical axis wind turbines can reduce load fluctuations during turbine operation; however, a helix has complicated three-dimensional geometry that can be difficult to manufacture resulting in expensive blades. A new blade configuration based on twisted straight blades that are mounted at an angle to the vertical, a cant, has been developed and tested in a wind tunnel in a number of different configurations and conditions. They offer the benefits of distributing the fluctuating aerodynamic loads, but incorporate a linear axis so that they can be manufactured at a comparable cost to simple straight blades. The power performance data from the tunnel testing show that canted blades have comparable power output to similar straight blades and that aerodynamic fences can be used to improve power performance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.197
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2011
Admission routes1
Has abstractyes

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